Anomaly-based Intrusion Detection in Industrial Data with SVM and Random Forests

24 July 2019

Papers citing "Anomaly-based Intrusion Detection in Industrial Data with SVM and Random Forests"

8 / 8 papers shown

Title
CTMBIDS: Convolutional Tsetlin Machine Based Intrusion Detection System for DDoS attacks in an SDN environment Rasoul Jafari Gohari Laya Aliahmadipour M. Rafsanjani AAML 28 1 0 05 Sep 2024
Deployment Challenges of Industrial Intrusion Detection Systems Konrad Wolsing Eric Wagner Frederik Basels Patrick Wagner Klaus Wehrle 25 1 0 04 Mar 2024
Online Transition-Based Feature Generation for Anomaly Detection in Concurrent Data Streams Yinzhen Zhong A. Lisitsa 22 0 0 17 Aug 2023
Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data Snehanshu Saha Jyotirmoy Sarkar S. Dhavala Santonu Sarkar Preyank Mota AI4TS 20 2 0 17 Feb 2023
On Explainability in AI-Solutions: A Cross-Domain Survey S. D. Antón Daniel Schneider Hans D. Schotten 23 2 0 11 Oct 2022
A False Sense of Security? Revisiting the State of Machine Learning-Based Industrial Intrusion Detection Dominik Kus Eric Wagner Jan Pennekamp Konrad Wolsing I. Fink Markus Dahlmanns Klaus Wehrle Martin Henze 29 24 0 18 May 2022
IPAL: Breaking up Silos of Protocol-dependent and Domain-specific Industrial Intrusion Detection Systems Konrad Wolsing Eric Wagner Antoine Saillard Martin Henze 21 31 0 05 Nov 2021
Investigating the Ecosystem of Offensive Information Security Tools S. D. Antón Daniel Fraunholz Daniel Schneider 17 2 0 16 Dec 2020